adjR2.glm {glmtoolbox} | R Documentation |
Adjusted R-squared in Generalized Linear Models
Description
Computes the adjusted deviance-based R-squared in generalized linear models.
Usage
## S3 method for class 'glm'
adjR2(..., digits = max(3, getOption("digits") - 2), verbose = TRUE)
Arguments
... |
one or several objects of the class glm, which are obtained from the fit of generalized linear models. |
digits |
an (optional) integer value indicating the number of decimal places to be used. As default, |
verbose |
an (optional) logical indicating if should the report of results be printed. As default, |
Details
The deviance-based R-squared is computed as . Then,
the adjusted deviance-based R-squared is computed as
, where
is the
number of parameters in the linear predictor and
is the sample size.
Value
a matrix with the following columns
Deviance | value of the residual deviance, |
R-squared | value of the deviance-based R-squared, |
df | number of parameters in the linear predictor, |
adj.R-squared | value of the adjusted deviance-based R-squared, |
Examples
###### Example 1: Fuel efficiency of cars
Auto <- ISLR::Auto
fit1 <- glm(mpg ~ horsepower*weight, family=Gamma(inverse), data=Auto)
fit2 <- update(fit1, formula=mpg ~ horsepower*weight*cylinders)
fit3 <- update(fit1, family=Gamma(log))
fit4 <- update(fit2, family=Gamma(log))
fit5 <- update(fit1, family=inverse.gaussian(log))
fit6 <- update(fit2, family=inverse.gaussian(log))
AIC(fit1,fit2,fit3,fit4,fit5,fit6)
BIC(fit1,fit2,fit3,fit4,fit5,fit6)
adjR2(fit1,fit2,fit3,fit4,fit5,fit6)
[Package glmtoolbox version 0.1.12 Index]